Synthesis of topologically-constrained water reuse network using swarm intelligence

The sustainability of water resources is one of the major concerns of the world population. As such, industries are finding ways to minimize the water withdrawals and to reduce the water pollution through efficient use of water supplies. Process water integration has focused on the reduction of the...

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Main Author: Hul, Seingheng
Format: text
Language:English
Published: Animo Repository 2006
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Online Access:https://animorepository.dlsu.edu.ph/etd_masteral/3534
https://animorepository.dlsu.edu.ph/context/etd_masteral/article/10372/viewcontent/CDTG004356_P.pdf
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_masteral-103722023-10-20T00:39:54Z Synthesis of topologically-constrained water reuse network using swarm intelligence Hul, Seingheng The sustainability of water resources is one of the major concerns of the world population. As such, industries are finding ways to minimize the water withdrawals and to reduce the water pollution through efficient use of water supplies. Process water integration has focused on the reduction of the amount of water used and water discharged. Water integration is done to determine both the minimum fresh water budget and wastewater released. The water network needed to get this minimum water usage was determined by establishing the reuse scheme, from the source streams to feed the sink streams. A procedure for designing reuse networks with topological, network complexity and stream matching constraints was developed. The procedure used particle swarm optimization (PSO) enhanced with genetic mutator. The result achieved by PSO was compared with commercial genetic algorithms (GA) package. Four main case studies with sub-cases were used to test PSO. The freshwater saving achieved by PSO and commercial GA package with the same number of function evaluations ranged from 6 - 54% and 1 - 43%, respectively. The amount of water saving varies depending on the cases conducted. PSO provided a better result than the commercial GA package. The PSO algorithm was further improved by introducing mutation to integer variables and seeding strategy. 2006-01-01T08:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etd_masteral/3534 https://animorepository.dlsu.edu.ph/context/etd_masteral/article/10372/viewcontent/CDTG004356_P.pdf Master's Theses English Animo Repository Swarm intelligence Mathematical optimization Genetic algorithms Water reuse Chemical Engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Swarm intelligence
Mathematical optimization
Genetic algorithms
Water reuse
Chemical Engineering
spellingShingle Swarm intelligence
Mathematical optimization
Genetic algorithms
Water reuse
Chemical Engineering
Hul, Seingheng
Synthesis of topologically-constrained water reuse network using swarm intelligence
description The sustainability of water resources is one of the major concerns of the world population. As such, industries are finding ways to minimize the water withdrawals and to reduce the water pollution through efficient use of water supplies. Process water integration has focused on the reduction of the amount of water used and water discharged. Water integration is done to determine both the minimum fresh water budget and wastewater released. The water network needed to get this minimum water usage was determined by establishing the reuse scheme, from the source streams to feed the sink streams. A procedure for designing reuse networks with topological, network complexity and stream matching constraints was developed. The procedure used particle swarm optimization (PSO) enhanced with genetic mutator. The result achieved by PSO was compared with commercial genetic algorithms (GA) package. Four main case studies with sub-cases were used to test PSO. The freshwater saving achieved by PSO and commercial GA package with the same number of function evaluations ranged from 6 - 54% and 1 - 43%, respectively. The amount of water saving varies depending on the cases conducted. PSO provided a better result than the commercial GA package. The PSO algorithm was further improved by introducing mutation to integer variables and seeding strategy.
format text
author Hul, Seingheng
author_facet Hul, Seingheng
author_sort Hul, Seingheng
title Synthesis of topologically-constrained water reuse network using swarm intelligence
title_short Synthesis of topologically-constrained water reuse network using swarm intelligence
title_full Synthesis of topologically-constrained water reuse network using swarm intelligence
title_fullStr Synthesis of topologically-constrained water reuse network using swarm intelligence
title_full_unstemmed Synthesis of topologically-constrained water reuse network using swarm intelligence
title_sort synthesis of topologically-constrained water reuse network using swarm intelligence
publisher Animo Repository
publishDate 2006
url https://animorepository.dlsu.edu.ph/etd_masteral/3534
https://animorepository.dlsu.edu.ph/context/etd_masteral/article/10372/viewcontent/CDTG004356_P.pdf
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